WTP & Simulations

Due: November 08 by 11:59pm

Weight: This assignment is worth 3% of your final grade.

Purpose: The purpose of this assignment is to introduce the concept of willingness to pay (WTP) and to learn how we can use estimated model coefficients to compute estimates of WTP and make predictions about how likely people would be to choose each option in a set of alternatives.

Assessment: This assignment is graded using a check system:

  • ✔+ (110%): Responses shows phenomenal thought and engagement with the course content. I will not assign these often.
  • ✔ (100%): Responses are thoughtful, well-written, and show engagement with the course content. This is the expected level of performance.
  • ✔− (50%): Responses are hastily composed, too short, and/or only cursorily engages with the course content. This grade signals that you need to improve next time. I will hopefully not assign these often.

Notice that this is essentially a pass/fail system. I’m not grading your writing ability and I’m not counting the number of words you write - I’m looking for thoughtful engagement. One or two sentences is not enough. Write at least a paragraph and show me that you did the readings assigned.

1. Get Organized

Download and edit this template when working through this assignment.

Then unzip the template folder (make sure you unzip it!), then open the .Rproj file to open RStudio. Open the hw9.Rmd file, take notes, and write some example code as you go through the following.

2. Readings

At this point in the class, we know how to design conjoint surveys, field them on formr.org, clean the resulting data, estimate models, and assess the uncertainty around the resulting coefficients. But what do those coefficients actually mean? How should we use them to gain design insights?

This week, we’ll begin considering these questions as we learn how to use estimated model coefficients to compute estimates of “willingness to pay” (WTP) and make predictions about how likely people would be to choose each option in a set of alternatives. Take notes as you watch the video on these topics, and answer the practice questions in the video as part of your reflection. You may submit your answers however you wish, e.g. hand-write them on paper and take a picture and / or type answers in your reflection .Rmd file.

Click here to download the slides in the video as a PDF.

3. Reflect

Reflect on what you’ve learned while going through these readings and exercises. Is there anything that jumped out at you? Anything you found particularly interesting or confusing? Write at least a paragraph in your hw9.Rmd file. Here are some suggestions:

  • Discuss some of the key insights or things you found interesting in the readings or recent class periods.
  • Write about the messiest data you’ve seen.
  • Connect the course content to your own work or project you’re working on.

4. Knit

Click the “knit” button to compile your hw9.Rmd file into a html web page. Then open the hw9.html file in a web browser and proofread your report. Does all of the formatting look correct?

5. Submit

To submit this assignment, create a zip file of all the files in your R project folder for this assignment. Name the zip file hw9-netID.zip, replacing netID with your netID (e.g., hw9-jph.zip). Then copy that zip file into the “submissions” folder in your Box folder created for this class.